Investigating and mapping spatial patterns of arsenic contamination in groundwater using regression analysis and spline interpolation technique

Abstract

The present study investigates the hypothesis that arsenic concentrations correlate with tubewell depth, and examines the effectiveness of spline interpolation, specifically completely regularized spline (CRS) and spline with tension (SWT) in estimating the magnitude of arsenic contamination in groundwater in Thanh Tri, a densely populated district located in the southern part of Hanoi City, Vietnam. Groundwater sampling conducted in 72 tubewells drilled into shallow aquifers yielded an average arsenic concentration of 82 μg/L with a maximum of 395 μg/L, far higher than the World Health Organization (WHO) guideline value of 10 μg/L. The average concentration in the lower Pleistocene aquifer was 86 μg/L, slightly higher compared with the average of 78 μg/L in the upper Holocene aquifer. Interestingly, regression analysis revealed that in the Holocene aquifer, depth of wells influenced arsenic concentrations significantly. Such an influence, however, was insignificant in the lower Pleistocene aquifer. Both the CRS and SWT spatial interpolation models resulted in plausible predictions for the arsenic concentration data. The problem of arsenic contamination in the study area should be considered seriously, as 99% of the area was estimated to be affected by arsenic levels exceeding the WHO guideline value.